Geospatial Distribution of Ambulatory Surgery Center Utilization for Otorhinolaryngologic Surgeries Among Medicare Patients From 2015 to 2019

Abstract Objective To investigate the geographic clustering of ambulatory surgical center (ASC) utilization in otolaryngology to determine hot spot areas of high utilization and cold spot areas of low utilization and socioeconomic factors that correlate with these hot spots and cold spots. Study Design To develop a national epidemiologic study of ASC utilization in otolaryngology in the United States. Setting United States of America. Methods Multiple county‐level national databases were reviewed including Center for Medicare Services (CMS) physician billing data, CMS Medicare demographic data, and US Census socioeconomic data. The analysis was conducted using the average of all Medicare billing information from 2015 to 2019. Whether a procedure was performed in an ASC was extracted from CMS data using the CMS definition of an ASC. The percentage ASC billing was calculated as the fraction of CMS payments that were performed in ASCs for the top ENT procedures. A Python‐based script for database building and GeoDa, Moran's I clustering coefficient, and a 1‐way analysis of variance was utilized to chart and analyze demographic, geographic, and socioeconomic trends. Results Hot spots of utilization, with an average ASC billing of 80.13%, were seen in Southern California, Florida, Mid‐Atlantic, and clusters throughout the Deep South. Cold spot clusters, with an average ASC billing of 2.21%, were located in large swaths of New England, Ohio, and the Deep South with clusters bisecting the Midwest. Cold spots had a higher percentage of poverty and percent eligible for Medicaid. Conclusion ASC utilization is best used to improve cost‐effectiveness and accessibility of care but what is seen is that ASC use is currently highest in cities in coastal areas which already have high levels of care access and are making the most proportional money compared to their rural counterparts.

S ince the 1980s, advancements in anesthesia and surgical care have made possible the shift of many types of surgical interventions from the inpatient setting to the outpatient (ambulatory) setting. In addition, these outpatient surgeries and procedures are less frequently occurring in hospital outpatient departments (HOPDs), facilities owned and generally attached to a hospital, and more often occurring in ambulatory surgery centers (ASCs), typically standalone facilities that are dedicated solely to high-throughput of same-day surgical care. Proponents have embraced the greater efficiency of these centers and their ability to significantly reduce costs to the health care system, while others have questioned the safety of moving an expanding number of procedures and procedure types to these centers.
In the United States, estimates for the fraction of surgeries done in the ambulatory setting vary greatly from 52% to 80% depending on the inclusion criteria. [1][2][3] Within otolaryngology, there are several surgeries that are usually or almost exclusively done in the ambulatory setting including tympanoplasty (97.4%), myringotomy (97.3%), mastoidectomy (87.2%), tonsillectomy and/or adenoidectomy (95.5%), plastic surgery procedures on nose (91.9%), and other nose, mouth, pharynx, and ear procedures (65.6%-69.7%). 2 The use of ambulatory surgical centers allows for great convenience for the patient. The mean length of stay for the ambulatory setting was 0.2 days while the inpatient mean was 6 days. On top of that, on average a procedure done in the ASC setting takes 31.8 minutes less than their inpatient counterparts. 3 These factors combined make the utilization of ASC an efficient and economical setting for procedures, especially as future demand increases.
Ophthalmology (36%), orthopedics (36%), and gastroenterology (32%) are the specialties that have embraced the transition to ASC most strongly and have the highest percentage of procedures done at these centers. Otolaryngology has also progressively transitioned to ASCs due to cost and accessibility benefits for the patients.
The goal of this study is to investigate the geographic clustering of ASC utilization in otolaryngology to determine hot spots of high utilization and socioeconomic factors that correlate with these hot spots and cold spots.

Data Sources, Collection, and Extraction
National, publicly available databases from the US government were combined for 2015 to 2019 to encompass the Medicare billing patterns of ear, nose, and throat (ENT) practitioners as well as the corresponding Medicare populations for each applicable county in the continental United States. Databases included: Center for Medicare Services (CMS) physician billing data, 4 CMS Medicare demographic data, 5 and US Census socioeconomic data. 6 Due to using only publicly available data, institutional review board or ethics committee approval was not applicable for this study. First, a list of the top 100 ENT procedure codes was extracted from the "Coding Corner," a resource from the American Academy of Otolaryngology-Head and Neck Surgery (AAO-HNS) to teach CMS coding to its members. For the list, AAO-HNS's "top 100" criteria was the total CMS billing amount for those instances of the procedure codes done in an ASC. We started with a list from AAO-HNS to ensure the procedure codes we studied were limited to those in the ENT specialty. Second, the aforementioned CMS physician billing data set 4 was then used to obtain information on these 100 procedure codes including the geographic locations they were performed, the total number of procedure services, and the fraction of the services performed at an ASC versus a HOPD. Third, the list of 100 procedure codes was further filtered to the 53 procedure codes that were performed at least once in an HOPD and at least once in an ASC. In this article, we use the term procedure codes to refer to CMS's Health Care Common Procedure Coding System (HCPCS codes) which are synonymous with Current Procedural Terminology codes in this context.
Multiple linear regressions were conducted across each of the studied variables for each county across the 5 years of billing between 2015 and 2019 to identify how these variables changed over time at a county-level granularity. Counties without billing of the chosen procedures in the time frame were removed from the analysis. The data set on Medicare demographic data 5 allowed for the countylevel approximation of the Medicare members within each billing area. Census data was used to identify populationlevel socioeconomic variables to further supplement the data set. Each database was grouped at a county level and then combined utilizing Python with GeoDa, a geospatial analysis software, used for map-based hot spot analysis and visualization. 7,8 We use the term county to indicate either legallydefined counties or "county-equivalents," which is a term used by the US Census Bureau that also includes certain edge cases: for example, Baltimore, MD and Washington, DC, which are not legally inside any county, and parishes, which Louisiana's legal equivalent to counties.

Statistical Analysis
Cluster analysis in GeoDa was conducted using Moran's I statistic. 9 Moran's I allow for a measure of significant spatial variation between counties across a variable of interest. The statistic groups each county into 1 of 4 statistically significant classifications for a variable of interest: high-high, low-low, low-high, and high-low. The first of the 2-part classification describes if a county's value of interest is statistically significantly higher or lower than the national average. The second part of the classification describes if a county's average neighbor's value of interest is significantly higher or lower than the national average. If both a county and its average neighbor are significant in either direction, then the county as a whole is significant according to Moran's I statistic. Highhigh and low-low grouping represent hot spots and cold spots respectively, while low-high and high-low groupings demarcate geospatial areas of incongruence. The neighbor designation is determined by the minimum distance between the centroids of counties to allow for each county to have at least 1 neighbor, which is approximately 100 miles.
The 4 significant Moran's I groupings of ambulatory surgical center utilization were then further analyzed using a 1-way analysis of variance across all county-level variables to identify disparities. A 2-tailed t test was then used to compare only high-high (hot spot) and low-low (cold spot) groupings.

National Level Statistics
After the removal of counties without billing data between 2015 and 2019, 941 counties in the continental United States remained. While this is only 29.9% of the . This is logical as the counties with insufficient CMS data to be included in our analysis were generally sparsely populated.
Of the top 100 billed procedure types, 53 were shared between ASC and HOPD facilities and thus were included in the analysis. The list of procedure types was diverse including "Diagnostic examination of voice box using flexible endoscope" to "Implantation of cochlear device" ( Table 1; Supplemental File 1, available online). The 53 procedure types could be generally categorized into 1 of 5 ENT subspecialties: 11 in facial plastics, 9 in head and neck surgery, 6 in otology, 17 in rhinology, and 10 in laryngology (10) ( Table 2).
A total of 1,233,099 procedures were found over the 5-year period. These procedures had a corresponding total Medicare payment amount of $320,317,240, which makes an average annual cost of $64,063,448 ( Figure 1). The costs increased an average of $2,730,352 (standard error [SE] $33,613) or 4.26% (SE 0.052%) per year. While ASCs only had 29.08% of the noted procedures, they comprised 62.54% of the total Medicare payment (Figures 1 and 2). The Medicare payment per service performed was higher in ASCs than HOPDs in all of the ENT subspecialties and in most of the HCPCS codes. This trend was also true regardless of how frequently or infrequently the procedure was performed in ASCs versus HOPDs ( Figure 3). The percent billing toward ASC increased by an average of 2.32% each year with the total ASC increasing by 0.1% on average per year.

Geographic Clustering
Geospatial clustering analysis of the percent of the top ENT procedures conducted in ASC per county is displayed in Figure 4B with the corresponding percent billing values shown in the adjoining Figure 4A. At p ≤ .05, 90 counties were identified as hot spot clusters and 33 as cold spot clusters ( Table 3). The counties that were identified as hot spots had an average percent ASC billing of 80.13%. Hot spots were seen in Southern California, Florida, Mid-Atlantic, and in small, scattered clusters throughout the Deep South. Cold spot clusters had an average percent ASC billing of 2.21% and were located in large swaths of New England/Northeast (Boston, New Hampshire), Ohio, and the Deep South with scattered clusters bisecting the Midwest longitudinally. Analysis of the percent change from 2015 to 2019 in ASC billing is displayed in Figure 5. Minimal clustering was seen on a national level. Small hot spots of change in ASC billing were scattered throughout the Rocky Mountains with an average 13.96% increase in billing over the time period. Cold spots, with an average decrease in ASC billing by 1.2%, were dispersed throughout Texas including the Huston metropolitan, the Great Lakes including the Chicago metropolitan, and the Rust Belt.

Correlates of Geographic Clusters
There were several statistically significant socioeconomic differences between hot spot and cold spot clusters of ASC billing that are displayed in Table 3. Notably, when compared to cold spots, hot spots were older (average Medicare age of 72.4 years old vs 70.4 years old, p ≤ .001) and more urban (1.92 vs 3.48 average RUCA classification, a measure of how rural a county is, p ≤ .001). Hot spots also had slightly greater rates of unemployment (4.8% vs 4.6%, p = .010). Cold spots had a higher percentage of poverty (14.0% vs 12.5%, p = .003) and a greater percentage of individuals eligible for Medicaid (23.9% vs 16.6%, p ≤ .001). Ethnic and racial factors were also different: hot spots contained greater percentages of African Americans (8.9% vs 4.1%, p ≤ .001) and Hispanics (5.8% vs 1.2%, p ≤ .001) and lower percentages of non-Hispanic whites (80.7% % vs 88.0%, p ≤ .001).
The main results that are discussed in this section include the geographic denotations of areas of high and low utilization, the geographic locations with the highest and lowest percent change in utilization, and the demographic difference between areas with high and low utilization.

Discussion
ASCs are a major variable in modern surgical care. Our data shows that utilization of ASCs from 2015 to 2019 was greatest in the western United States, the mid-Atlantic, and Florida ("hot spots"). Relative to their neighbors, they were least in the Midwest and upper Northeast ("cold spots"). However, the central United States, including both major cities and rural areas, generally had lower utilization than the coasts. Central metropolitan areas like those of Chicago and Houston had a decreasing slope of utilization compared to their neighbors.
The benefit of the utilization of ASC is its costeffectiveness and ability to do procedures outside of large hospitals. Though there have been no studies that have investigated the ability of ambulatory surgical centers to improve access to surgical care, we can reasonably expect that the ability to perform outpatient procedures more efficiently could translate to more affordable care and improved operating cost in low-resource settings. Ideally, this would allow for increased accessibility to care for those populations that have low access to hospital institutions. Medicare reimbursement of ASC has been done as part of the Medicare goal of cost-cutting and increasing rural involvement. On the contrary, most utilization of ASC currently is in cities in coastal areas that already have high levels of care access and are making the most proportional money compared to their rural counterparts. Among the coastal regions, the upper northeast (Boston) are cold spot regions indicating, that they have significantly lower utilization than their neighbors. Ambulatory surgical centers may allow for increased access to care, especially in cold spots with poor access to hospital care. When looking at safety, it is important to note that these areas consist of vulnerable populations. There is evidence that ambulatory surgical centers can be as safe as or safer than their hospital counterparts. One study looking at Medicare data between 1994 and 1999 found that the overall adverse event rates leading to an emergency department visit were lowest in free-standing ambulatory-surgery centers when compared to other counterparts. 9 It is important to note that there are limitations of patient selection when it comes to ambulatory surgical care. A subsection of patients with comorbidities or poor health will require the setting of a hospital to receive their procedural care. When examining the demographic data, significant differences were also found between hot spots and cold spots. In the demographic data, starting with age, the hot spots population was a significant 2 years older than the cold spots. There is a trend in the increasing age of the otolaryngology patient population which could impact this difference in age as well. 10 Individuals in cold spots tended to have lower salaries, and cold spots had a higher percentage of poverty (14% compared to 12.5%) when compared to hot spot areas. These factors impact the access and quality of care patients receive. 11 When comparing differences in race composition, the cold spots were associated with a greater percentage of non-Hispanic whites. To note the hot spots tend to be located in more urban areas and the data analysis resolution did not consider intercity variation to access to care. It is possible that different areas of urban locations could have different demographics with different access to care. According to Healthy People 2030, the US government is failing in its goal to reduce the proportion of people unable to obtain needed medical care based on the most recent data published in 2018 to 8.7% from 4.1% in 2017. 12,13 In the advent of telemedicine, the ability to provide care to patients that would otherwise have to travel long distances to see a primary care physician. As telemedicine develops, access to primary providers will improve. This is especially true as wireless infrastructure continues to develop with government assistance. 14 As tools to improve access to primary care improves, there is still a need for improvement to simple procedural care. Ambulatory surgical centers could allow for improved access to uncomplicated procedural care. Government subsidies and hospital funding incentives to fund these centers would be an investment in the long term due to their cost-saving benefits. Also, government-funded physician incentives to practice in these centers at least      part-time would be beneficial. Note ACS should not replace procedural care for complicated patients that would need more advanced medical infrastructure for their care.
Although we used the top 53 billing codes, the amount of money per code was not evenly distributed and certain billing codes made the vast majority of money ( Table 3). The billing codes that were found to make the most were also found to be mostly done in the ASC setting. One interesting point is that the billing code with the most amount of money has a % ASC billing slope that is shallower compared to the other high-money billing codes. The procedure with the steepest % ASC billing slope is "removal of nasal air passage" (which refers to the submucosal resection of the inferior turbinate), which has been shown to have quite low complication rates in the ASC setting. 15 There are a few limitations to our study. The first is that the data set is based on Medicare data only, which may not reflect the general population at large. Thus, with the present data, we are cautious to generalize our recommendations to non-Medicare practice populations. This can be an area for future research. Another limitation is that some counties did not have categorized ENT billing data between 2015 and 2019 associated with them. These counties were sparsely populated. Therefore, we were forced to exclude these counties from the study, and they did not contribute to the determination of hot spots or cold spots. However, geographical areas that do not comprise ENT Medicare billing could have low access to procedures in both ASC and hospital settings. Another limitation is that some areas that have low utilization of ASC could be due to better access to procedures in the hospital setting. In this scenario, these areas would have great access to ENT procedures, but just not in the ASC setting.

Conclusion
The future of ASC utilization in otolaryngology is multifaceted. As ASC utilization in this field increases, considerations should be made to implement them in areas like those denoted as cold spot locations in this study. This may allow for improved access to this category of care including non-complex otolaryngological procedures. Although the full extent of the ability of ACS to improve access to surgical care is not fully understood this setting allows for shorter procedures and stays compared to hospital settings assuming that the quality of care is not compromised. These factors could possibly translate to more affordable care in these locations. Future work includes expanding the data sources from Medicare to improve the generalizability of the study. Also, improving the resolution of the study would allow for better investigation of intercity variation to access and their demographic characteristics. Finally, an investigation into the variation of procedures done in the ASC The rate indicates the annual amount of change as defined by the slope of the  setting in hot spots compared to cold spots should be done to see if there is a significant difference in the types of procedures done.

Author Contributions
Mark Nyaeme, interpreted the geospatial analysis results and drafted the introduction, results and discussion, conclusion, and limitations sections of the manuscript; Rahul S. Yerrabelli, interpreted the geospatial analysis results and drafted the introduction, results and discussion, conclusion, and limitations sections of the manuscript, performed the created code, Moran's statistical analysis, produced all figures, and produced all tables; Nicholas Peterman, extracted the data from publicly available sources, compiled it into a machine-readable format and drafted the methods; Brad Kaptur, edited the manuscript, and contributed to the conception and planning of the project; Eunhae Yeo, edited manuscript and contributed to the conception and planning of the project; Kristine R. Carpenter, is a practicing physician and provided clinical insight, edits to the manuscript, and supervision of the project.

Disclosures
Competing interests: The authors deny any financial or ethical conflicts of interest. Specifically, no authors have financial ties or ownership of surgical centers.
Funding source: The authors declare that no funds, grants, or other support were received specifically for the preparation of this manuscript.

Data Availability Statement
The original data sets used are available publicly. The compiled, machine-readable formatting of the data set is available from the corresponding author on request and will be made publicly available after the publication of this manuscript.